Clustered Scaling

Exploring Emerging Online Health Communities

As articulated in our Barriers section, the default position across the digital world is to aim for scale, with the apex predator in this space being the monopolistic unicorn organisation that just moments ago was a tech startup. Success in the world of online healthcare appears to require the opposite: a myriad of small entities who differentiate themselves through their granular expertise or focus and where a winner takes all outcome would mean that everyone loses. So, how we support organisations moving from thinking scaling is a feature to realising it is, in the main part, a bug is key to the sector’s development.

From the research a hypothesis is emerging focused on the idea of clustered scaling. We are using the terms clustered scaling to describe the dynamics of group formation described in the two Barriers of finance and business models constrain and scale is a bug not a feature as a way to enable online health communities through embracing each community’s natural socio-technical limits.

The idea is:

Clustered scaling occurs when each group has its own internal dynamics and internal network effects. Neither network effects not internal dynamics scale from cluster to cluster

Clustered scaling is a form of forking and this is part of its value to its group of users

Clustered scaling grows more slowly than classic scaling

It is even harder to abstract economic value from clustered scaling because of the heterogeneity across clusters.

The size and rate of growth for each cluster depends on:

The size of the internal network effects i.e. the internal virality ratio

Incentives internal to the cluster – for example Patients Like Me having a relationship with a Pharma firm that is interested in a particular disease; or an NHS trust that is strongly committed to local use of Patient Opinion.

Clustered scaling is expressed visually below.

It is likely that the differential network effects stem primarily from social effects rather than technological ones (i.e. groups have little interest in one another, indeed that may want to erect boundaries to protect their privacy).

Weak network effects within each cluster and almost none between clusters

External incentives often being driven by the business model

Increasing cluster size increases internal transaction costs, due to factors such as moderation, members’ requirements for real intimacy and quality of contributions.

By accepting clustered scaling as a route to optimising online health communities we depart from a perverse journey, towards bigger, that is never able to succeed, and instead turn towards a path of appropriately scaled communities that are fit for purpose and that, by placing ontology over epistemology, prioritise people over profit and process over output.